Open AccessARI(1,1) Model for Predicting Covid19 in Indonesia
Author(s) -
Nanda Rizqia Pradana Ratnasari
Publication year - 2020
Publication title -
indonesian journal of life sciences
Language(s) - English
Resource type - Journals
ISSN - 2656-0682
DOI - 10.54250/ijls.v2i2.51
Subject(s) - autoregressive model , statistics , covid-19 , maximum likelihood , econometrics , mathematics , geography , medicine , disease , pathology , infectious disease (medical specialty)
Covid19 modelling is needed to help people understanding the distribution or pattern of the data and doing the prediction. The data used for modelling in this study was ‘confirmed cases’ of Covid19 in Indonesia recorded from March 2 to August 23, 2020. Model obtained from analysis was ARI(1,1) with estimated parameter 0.9859 and standard error 0.0114. Maximum Likelihood was the method conducted to estimate the parameters. The model was good to predict the actual data of Covid19 confirmed cases in Indonesia.
Keywords: Covid19, autoregressive, prediction.